Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning reasoning and self-correction. Sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans.
Artificial intelligence, defined as intelligence exhibited by machines, has many applications in today’s society. More specifically, it is Weak AI, the form of AI where programs are developed to perform specific tasks, that are being utilized for a wide range of activities including medical diagnosis, electronic trading platforms, robot control, and remote sensing. AI has been used to develop and advance numerous fields and industries, including finance, healthcare, education, transportation, and more.
We are here to know about step AI climbing up to the healthcare sector.
Medical artificial intelligence (AI) mainly uses computer techniques to perform clinical diagnoses and suggest treatments. AI has the capability of detecting meaningful relationships in a data set and has been widely used in many clinical situations to diagnose, treat, and predict the results. The purpose of this special issue is to demonstrate the potential of several intelligent approaches exploited in medical informatics technologies and applications. Submissions for this special issue should be original work that deals in some manner with topics relevant to medical artificial intelligence, expert systems, data mining, machine learning, and image processing.
The main focus of this special issue will be on the proposal of techniques for medical artificial intelligence, expert systems, data mining, machine learning, and image processing which could be built on top of them. This special issue will become an international forum for researchers to summarize the most recent developments in the field, with a special emphasis given to the improvements and results obtained within the last several years.
AI Enters the Nursing Arena
Artificial intelligence (AI) is a relatively new concept in healthcare, particularly in nursing practice. Other once-revolutionary technologies developed for high quality, safe patient care are now commonplace in care delivery and education, ranging from electronic health record (EHR) to mobile health (mHealth), telehealth and sensors for remote patient monitoring and simulation. New data-driven, intelligent innovations in the healthcare space bring capabilities and the hope of adding value to nursing care delivery. Big tech companies entering the healthcare AI arena including IBM Watson, Microsoft, and Intel join other prominent industry players such as Google and Amazon to use Big Data-enabled AI solutions for more accurate image recognition, amplified web searching and to enhance the e-commerce experience. AI in healthcare is gaining traction, and nurses can harness its power to enhance standard patient care processes and workflows to improve quality of care, impact cost and optimize the patient and provider experience.
Sectors, where AI are being currently being used in healthcare, are:
- Disease Diagnosis
- Electronic Health Record
- Drugs interactions
Other tasks in medicine that can potentially be performed by artificial intelligence and are beginning to be developed include:
- Computer-aided interpretation of medical images. Such systems help scan digital images, e.g. from computed tomography, for typical appearances and to highlight conspicuous sections, such as possible diseases. A typical application is the detection of a tumor.
- Heart sound analysis
- Companion robots for the care of the elderly
- Mining medical records to provide more useful information.
- Design treatment plans.
- Assist in repetitive jobs including medication management.
- Provide consultations.
- Drug creation
- Using avatars in place of patients for clinical training
- Predict the likelihood of death from surgical procedures
- Predict HIV progression
Ways AI would help in healthcare
UNIFYING MIND AND MACHINE THROUGH BRAIN-COMPUTER INTERFACES
Using computers to communicate is not a new idea by any means, but creating direct interfaces between technology and the human mind without the need for keyboards, mice, and monitors is a cutting-edge area of research that has significant applications for some patients.
DEVELOPING THE NEXT GENERATION OF RADIOLOGY TOOLS
Radiological images obtained by MRI machines, CT scanners, and x-rays offer non-invasive visibility into the inner workings of the human body. But many diagnostic processes still rely on physical tissue samples obtained through biopsies, which carry risks including the potential for infection.
EXPANDING ACCESS TO CARE IN UNDERSERVED OR DEVELOPING REGIONS
Shortages of trained healthcare providers, including ultrasound technicians and radiologists can significantly limit access to life-saving care in developing nations around the world.
REDUCING THE BURDENS OF ELECTRONIC HEALTH RECORD USE
EHRs have played an instrumental role in the healthcare industry’s journey towards digitalization, but the switch has brought myriad problems associated with cognitive overload, endless documentation, and user burnout.
CONTAINING THE RISKS OF ANTIBIOTIC RESISTANCE
Antibiotic resistance is a growing threat to populations around the world as the overuse of these critical drugs fosters the evolution of superbugs that no longer respond to treatments. Multi-drug resistant organisms can wreak havoc in the hospital setting, and claim thousands of lives every year.
BRINGING INTELLIGENCE TO MEDICAL DEVICES AND MACHINES
Smart devices are taking over the consumer environment, offering everything from real-time video from the inside of a refrigerator to cars that can detect when the driver is distracted.
ADVANCING THE USE OF IMMUNOTHERAPY FOR CANCER TREATMENT
Immunotherapy is one of the most promising avenues for treating cancer. By using the body’s immune system to attack malignancies, patients may be able to beat stubborn tumors. However, only a small number of patients respond to current immunotherapy options, and oncologists still do not have a precise and reliable method for identifying which patients will benefit from this option.
TURNING THE ELECTRONIC HEALTH RECORD INTO A RELIABLE RISK PREDICTOR
EHRs are a goldmine of patient data, but extracting and analyzing that wealth of information in an accurate, timely, and reliable manner has been a continual challenge for providers and developers.
REVOLUTIONIZING CLINICAL DECISION MAKING WITH ARTIFICIAL INTELLIGENCE AT THE BEDSIDE
As the healthcare industry shifts away from fee-for-service, so too are it moving further and further from reactive care. Getting ahead of chronic diseases, costly acute events, and sudden deterioration is the goal of every provider – and reimbursement structures are finally allowing them to develop the processes that will enable proactive predictive interventions.
Artificial Intelligence is improving the healthcare industry. From predictive medical care and more accurate diagnosis to motivating the patients to take care of their health, AI will certainly continue enhancing the patient experience and healthcare expertise in general.